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In this paper, a hybrid method for occlusion removal using Finite element based Bi-dimensional Empirical Mode Decomposition (FE-BEMD) and Exemplar based image inpainting is discussed. Initially, the image is decomposed into Intrinsic Mode Functions (IMFs) and a Residue using FE-BEMD. Then the Exemplar based image inpainting algorithm is applied to each of the IMFs and residue and the results are added together to get the inpainted image. The results obtained shows that the proposed method works well for removing large objects as well as small damages like scratches from images. General Terms Image decomposition, occlusion removal from images. Keywords Image inpainting, Empirical Mode Decomposition, Intrinsic Mo-de Function, Delaunay Triangles, Texture synthesis, simultaneo-us structure and texture propagation. 1. INTRODUCTION Most of our historical data are in the form of images. Human and environmental factors can affect these images and damage them. The technique of filling-in the missing data in a damaged image in a visually plausible way is called image inpainting. It is also called disocclusion or image completion. Image inpainting is usually used to repair the damaged portions in a picture and also to remove unwanted objects from a picture, like overwriting. Its applications include restoration of old photographs, films and paintings and also cleaning documents. FE-BEMD is a fully data-driven, unsupervised decomposition method that decomposes images into Intrinsic Mode Functions and Residue. When all the IMFs are obtained, the data is actually decomposed into a number of frequency bands, in a nonlinear sense, as this method handles non-stationary signals. The lower IMFs pertain to the edges and higher IMFs pertain to illumination. This paper discusses a method that removes large objects as well as small damages like scratches from images, by applying exemplar based image inpainting to the IMFs and residue obtained by FE-BEMD of the images. The paper is organized as follows. Section 2 describes some of the existing inpainting methods. Section 3 deals with Finite Element based Bi-Dimensional Empirical Mode Decomposition. Section 4 describes exemplar based Image inpainting using FE-BEMD and Section 5 gives the experimental results. The last section provides the conclusion.

FEBEMD and Exemplar based Hybrid Image Inpainting for Occlusion Removal